This is a feature and bug release. Added AbsorbingLS which allows a large number of variables to be absorbed. This model can handle very high-dimensional dummy variables and has been tested using up to 1,000,000 categories in a data set with 5,000,000 observations. Fixed a bug when estimating weighted panel models that have repeated observations (i.e., more than one observation per entity and time id). Added drop_absorbed option to PanelOLS which automatically drops variables that are absorbed by fixed effects. Added optional Cythonized node selection for dropping singletons Added preconditioning to the dummy variable matrix when use_lsmr=True in fit. In models with many effects, this can reduce run time by a factor of 4 or more.